Begin by examining the data set. Recognize how the data is recorded and how you may be able to use the given data to explore potential relationships between categories.
Scatterplot Questions
1. Create a scatterplot using categories that you feel may influence fuel efficiency. Answer the following questions.
Identify the two categories you chose and why you thought there might be a relationship between the two BEFORE creating the scatterplot?
Answer:weight and city mpg- heavier the car, less mpg
Create the scatterplot. Which category is your x-axis and which is your y-axis? Why did you create your scatterplot in that order?
Answer:x: weight, y: city mpg. weight being the independent variable
Do you believe there is a relationship between the two categories? Why or why not?
Answer:yes, that one would effect the other
If there appears to be a relationship, does it have a positive or negative slope? What does this mean about the relationship between the two categories?
Answer:negative, more the weight, then less city mpg
Regression Questions
Create the linear regession equation in Excel. Include both the equation and the r2 value on the graph. Answer the following questions.
What is your regression equation? Explain what the equation means in relation to the categories.
Answer:power
What is your r2 value? Is this a strong correlation? Why or Why not?
Answer:.8065, yes, closer to 1 than the other equations
Based on all the information you have, can you make any conclusions about your two categories? If so, what conclusions can you make? If not, why not?
Answer:
Analysis
Right click on the regression equation and select "Format Trendline". Explore the different variations of regression equations.
How would you determine which equation had the best relationship?
Answer:compare the r squared values
Was the "Linear" option the optimal option? If so, why? If not, what was the better equation and why?
Answer:
Attach your Scatter Plots and Regression Information. Make sure your X and Y axis are correctly labeled. You may use Screen Shots to do so.
Begin by examining the data set. Recognize how the data is recorded and how you may be able to use the given data to explore potential relationships between categories.
Scatterplot Questions
1. Create a scatterplot using categories that you feel may influence fuel efficiency. Answer the following questions.
Answer:weight and city mpg- heavier the car, less mpgIdentify the two categories you chose and why you thought there might be a relationship between the two BEFORE creating the scatterplot?
Answer:x: weight, y: city mpg. weight being the independent variableCreate the scatterplot. Which category is your x-axis and which is your y-axis? Why did you create your scatterplot in that order?
Answer:yes, that one would effect the otherDo you believe there is a relationship between the two categories? Why or why not?
Answer:negative, more the weight, then less city mpgIf there appears to be a relationship, does it have a positive or negative slope? What does this mean about the relationship between the two categories?
Regression Questions
Create the linear regession equation in Excel. Include both the equation and the r2 value on the graph. Answer the following questions.
Answer:powerWhat is your regression equation? Explain what the equation means in relation to the categories.
Answer:.8065, yes, closer to 1 than the other equationsWhat is your r2 value? Is this a strong correlation? Why or Why not?
Answer:Based on all the information you have, can you make any conclusions about your two categories? If so, what conclusions can you make? If not, why not?
Analysis
Right click on the regression equation and select "Format Trendline". Explore the different variations of regression equations.
Answer:compare the r squared valuesHow would you determine which equation had the best relationship?
Answer:Was the "Linear" option the optimal option? If so, why? If not, what was the better equation and why?
Attach your Scatter Plots and Regression Information. Make sure your X and Y axis are correctly labeled. You may use Screen Shots to do so.